DocumentCode :
2340714
Title :
The application of combinatorial optimization by Genetic Algorithm and Neural Network
Author :
Zhou, Shiqiong ; Kang, Longyun ; Guo, Guifang ; Zhang, Yanning ; Cao, Jianbo ; Cao, Binggang
Author_Institution :
Sch. of Mech. Eng., Xi´´an Jiaotong Univ., Xi´´an
fYear :
2008
fDate :
3-5 June 2008
Firstpage :
227
Lastpage :
231
Abstract :
A optimization model of sizing the storage section in a renewable power generation system was set up, and two methods were used to solve the model: genetic algorithm or combinatorial optimization by genetic algorithm and neural network. The system includes the photovoltaic arrays, the lead-acid battery and a flywheel. The optimal sizing can be considered as a constrained optimization problem: minimization the total capacity of energy storage system, subject to the main constraint of the loss of power supply probability (LPSP). Both of the two optimal algorithm got good results. We can see that, combinatorial optimization by genetic algorithm and neural network can lessen the calculation time, with the results change little.
Keywords :
combinatorial mathematics; electric power generation; energy storage; flywheels; genetic algorithms; lead acid batteries; neural nets; renewable energy sources; solar cell arrays; combinatorial optimization; energy storage system capacity; flywheel; genetic algorithm; lead-acid battery; neural network; photovoltaic arrays; power supply probability loss; renewable power generation methods system; Batteries; Capacity planning; Constraint optimization; Flywheels; Genetic algorithms; Neural networks; Optimization methods; Photovoltaic systems; Power system modeling; Solar power generation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics and Applications, 2008. ICIEA 2008. 3rd IEEE Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1717-9
Electronic_ISBN :
978-1-4244-1718-6
Type :
conf
DOI :
10.1109/ICIEA.2008.4582512
Filename :
4582512
Link To Document :
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